A High-Frequency and Real-Time Ground Remote Sensing System for Obtaining Water Quality Based on a Micro Hyper-Spectrometer.

The safeguarding of scarce water resources is critically dependent on continuous water quality monitoring. Traditional methods like satellite imagery and automated underwater observation have limitations in cost-efficiency and frequency. Addressing these challenges, a ground-based remote sensing system for the high-frequency, real-time monitoring of water parameters has been developed. This system is encased in a durable stainless-steel shell, suited for outdoor environments, and features a compact hyperspectral instrument with a 4 nm spectral resolution covering a 350-950 nm wavelength range. In addition, it also integrates solar power, Wi-Fi, and microcomputers, enabling the autonomous long-term monitoring of water quality. Positioned on a rotating platform near the shore, this setup allows the spectrometer to quickly capture the reflective spectrum of water within 3 s. To assess its effectiveness, an empirical method correlated the reflective spectrum with the actual chlorophyll a(Chla) concentration. Machine learning algorithms were also used to analyze the spectrum's relationship with key water quality indicators like total phosphorus (TP), total nitrogen (TN), and chemical oxygen demand (COD). Results indicate that the band ratio algorithm accurately determines Chla concentration (R-squared = 0.95; RMSD = 0.06 mg/L). For TP, TN, and COD, support vector machine (SVM) and linear models were highly effective, yielding R-squared values of 0.93, 0.92, and 0.88, respectively. This innovative hyperspectral water quality monitoring system is both practical and reliable, offering a new solution for effective water quality assessment.

scATAC-Ref: a reference of scATAC-seq with known cell labels in multiple species.

Chromatin accessibility profiles at single cell resolution can reveal cell type-specific regulatory programs, help dissect highly specialized cell functions and trace cell origin and evolution. Accurate cell type assignment is critical for effectively gaining biological and pathological insights, but is difficult in scATAC-seq. Hence, by extensively reviewing the literature, we designed scATAC-Ref (https://bio.liclab.net/scATAC-Ref/), a manually curated scATAC-seq database aimed at providing a comprehensive, high-quality source of chromatin accessibility profiles with known cell labels across broad cell types. Currently, scATAC-Ref comprises 1 694 372 cells with known cell labels, across various biological conditions, >400 cell/tissue types and five species. We used uniform system environment and software parameters to perform comprehensive downstream analysis on these chromatin accessibility profiles with known labels, including gene activity score, TF enrichment score, differential chromatin accessibility regions, pathway/GO term enrichment analysis and co-accessibility interactions. The scATAC-Ref also provided a user-friendly interface to query, browse and visualize cell types of interest, thereby providing a valuable resource for exploring epigenetic regulation in different tissues and cell types.

Non-contact high precision pulse-rate monitoring system for moving subjects in different motion states.

Remote photoplethysmography (rPPG) enables contact-free monitoring of the pulse rate by using a color camera. The fundamental limitation is that motion artifacts and changes in ambient light conditions greatly affect the accuracy of pulse-rate monitoring. We propose use of a high-speed camera and a motion suppression algorithm with high computational efficiency. This system incorporates a number of major improvements including reproduction of pulse wave details, high-precision pulse-rate monitoring of moving subjects, and excellent scene scalability. A series of quantization methods were used to evaluate the effect of different frame rates and different algorithms in pulse-rate monitoring of moving subjects. The experimental results show that use of 180-fps video and a Plane-Orthogonal-to-Skin (POS) algorithm can produce high-precision pulse-rate monitoring results with mean absolute error can be less than 5 bpm and the relative accuracy reaching 94.5%. Thus, it has significant potential to improve personal health care and intelligent health monitoring.

Establishment and Application of a Patient-Ventilator Asynchrony Remote Network Platform for ICU Mechanical Ventilation: A Retrospective Study.

BACKGROUND: In the process of mechanical ventilation, the problem of patient-ventilator asynchrony (PVA) is faced. This study proposes a self-developed remote mechanical ventilation visualization network system to solve the PVA problem. METHOD: The algorithm model proposed in this study builds a remote network platform and achieves good results in the identification of ineffective triggering and double triggering abnormalities in mechanical ventilation. RESULT: The algorithm has a sensitivity recognition rate of 79.89% and a specificity of 94.37%. The sensitivity recognition rate of the trigger anomaly algorithm was as high as 67.17%, and the specificity was 99.92%. CONCLUSIONS: The asynchrony index was defined to monitor the patient's PVA. The system analyzes real-time transmission of respiratory data, identifies double triggering, ineffective triggering, and other anomalies through the constructed algorithm model, and outputs abnormal alarms, data analysis reports, and data visualizations to assist or guide physicians in handling abnormalities, which is expected to improve patients' breathing conditions and prognosis.

Cervical cell classification with deep-learning algorithms.

Cervical cancer is a serious threat to the lives and health of women. The accurate analysis of cervical cell smear images is an important diagnostic basis for cancer identification. However, pathological data are often complex and difficult to analyze accurately because pathology images contain a wide variety of cells. To improve the recognition accuracy of cervical cell smear images, we propose a novel deep-learning model based on the improved Faster R-CNN, shallow feature enhancement networks, and generative adversarial networks. First, we used a global average pooling layer to enhance the robustness of the data feature transformation. Second, we designed a shallow feature enhancement network to improve the localization and recognition of weak cells. Finally, we established a data augmentation network to improve the detection capability of the model. The experimental results demonstrate that our proposed methods are superior to CenterNet, YOLOv5, and Faster R-CNN algorithms in some aspects, such as shorter time consumption, higher recognition precision, and stronger adaptive ability. Its maximum accuracy is 99.81%, and the overall mean average precision is 89.4% for the SIPaKMeD and Herlev datasets. Our method provides a useful reference for cervical cell smear image analysis. The missed diagnosis rate and false diagnosis rate are relatively high for cervical cell smear images of different pathologies and stages. Therefore, our algorithms need to be further improved to achieve a better balance. We will use a hyperspectral microscope to obtain more spectral data of cervical cells and input them into deep-learning models for data processing and classification research. First, we sent training samples of cervical cells into our proposed deep-learning model. Then, we used the proposed model to train eight types of cervical cells. Finally, we utilized the trained classifier to test the untrained samples and obtained the classification results. Fig 1. Deep-learning cervical cell classification framework.

Open-source mobile multispectral imaging system and its applications in biological sample sensing.

Visible-near-infrared spectroscopy data can be utilized as an important quantitative indicator of biomolecular quantitative analysis. When acquiring spectral information, hyperspectral/multispectral imaging systems can obtain the spatial information of the object of interest. This allows the complete spatial-spectral information of the object of interest to be acquired and the spatial distribution of biomolecules to be analyzed. In this study, we present an open-source mobile multispectral imaging system, test the influence of the utilization of LEDs on the multispectral image, and design image-processing algorithms to correct this influence. Todemonstrate the effectivenessofthesystem, the system is applied to meat freshness analysis, small-animal tumor in-vivo imaging, and chlorophyll spatial distribution imaging. The experimental results verify that our system has stable performance and is compatible with a wide range of spectral imaging applications.

Smartphone imaging spectrometer for egg/meat freshness monitoring.

Data transmission between spectroscopy equipment and mobile terminals is critical to realising hand-held field-level monitoring. Currently, on-the-go (OTG) communication technology is a convenient and efficient method of data transmission for mobile devices. However, few people associate spectroscopy equipment with smartphones through the OTG port. This study developed a portable imaging spectrometer with a spectral resolution of approximately 12 nm in the visible-near-infrared band (400-1000 nm). It can be connected to a smartphone through the USB-OTG port to process the spectral signal through the smartphone's system on a chip (SoC). It also displays real-time spectral images of the food samples through the smartphone's screen. Using a support vector machine (SVM) to classify the spectra of the various experimental samples (e.g. eggs and pork), the model prediction accuracy rate is approximately 90%. This further proves the reliability of the proposed smartphone imaging spectrometer for monitoring the freshness of food samples onsite.

Isolation, Identification, and Anti-Inflammatory Activity of Polysaccharides of Typha angustifolia.

The present study aimed to purify, structurally characterize, and evaluate the anti-inflammatory activity of the polysaccharide extracted from Typha angustifolia. Two purified polysaccharides (PTA-1 and PTA-2) were obtained via DEAE-52 cellulose chromatography. Their structural characterizations and antioxidant activity were in vitro analyzed. To evaluate the anti-inflammatory activity of PTA-2, the levels of inflammatory cytokines, intracellular ROS production, and the inhibitory effects of the transcriptional activation of the nuclear factor kappa B (NF-κB) signaling pathway were determined. PTA-1 comprises glucose (100%) with α-(1 → 3) glycosidic bonds, and PTA-2 comprises glucose (66.7%) and rhamnose (33.3%) formed by ß-(1 → 3) glycosidic bonds. PTA-1 and PTA-2 showed strong antioxidant activity in vitro. Moreover, PTA-2 intervention (50, 100, and 200 µg/mL) suppressed the production of inflammatory cytokines, the activation of NF-κB signaling, and reactive oxygen species production significantly. The results identified PTA-2 as a natural product that could be applied in anti-inflammatory drugs.

Light-Sheet Microscopy for Surface Topography Measurements and Quantitative Analysis.

A novel light-sheet microscopy (LSM) system that uses the laser triangulation method to quantitatively calculate and analyze the surface topography of opaque samples is discussed. A spatial resolution of at least 10 µm in z-direction, 10 µm in x-direction and 25 µm in y-direction with a large field-of-view (FOV) is achieved. A set of sample measurements that verify the system's functionality in various applications are presented. The system has a simple mechanical structure, such that the spatial resolution is easily improved by replacement of the objective, and a linear calibration formula, which enables convenient system calibration. As implemented, the system has strong potential for, e.g., industrial sample line inspections, however, since the method utilizes reflected/scattered light, it also has the potential for three-dimensional analysis of translucent and layered structures.

Isolation and identification of polysaccharides from Pythium arrhenomanes and application to strawberry fruit (Fragaria ananassa Duch.) preservation.

In this study, we extracted exopolysaccharides from Pythium arrhenomanes and purified them to obtain three polysaccharides (PEPS-1, PEPS-2, PEPS-3). The composition of these polysaccharides was determined. PEPS-2 and PEPS-3 showed outstanding antioxidant activities. PEPS-2 was chosen as a polysaccharide-based coating for strawberry fruit, and its effects on postharvest preservation of the fruit were determined. Strawberries coated with PEPS-2 exhibited significant delay in decay index and lower malondialdehyde, higher soluble solids content, anthocyanin content and vitamin C content, and greater DPPH radical-scavenging activity than uncoated control fruit. The developed method could be beneficial for improving the shelf-life of strawberries.

Non-invasive and rapid pH monitoring for meat quality assessment using a low-cost portable hyperspectral scanner.

It has been demonstrated that optical spectroscopy is a powerful tool for the quantitative monitoring of the main chemical components in food. However, portable spectrometer for on-site food quality assessment has rarely been reported. Here, a low-cost and portable hyperspectral scanner is developed. Utilizing this hyperspectral scanner by handheld push-broom scanning, reflectance spectra of meat samples can be obtained non-invasively and rapidly. Support vector regression (SVR) model is used to predict the pH value. The prediction accuracy rate of the model is close to 90%, and the coefficient of determination is about 0.93, which shows the feasibility of this system in on-site monitoring pH of meat.

SAT: Free Software for the Semi-Automated Analysis of Rodent Brain Sections With 2,3,5-Triphenyltetrazolium Chloride Staining.

Ischemic stroke places an increasing burden on individuals, families, and societies around the world. However, effective therapies or drugs for ischemic stroke are lacking. Therefore, animal models mimicking ischemic stroke in humans are of great value for preclinical experiments. middle cerebral artery occlusion (MCAO) in mice or rats and subsequent 2,3,5-triphenyltetrazolium chloride (TTC) staining of brain sections are common methods in the study of experimental animal ischemic stroke. In this study, we present and assess the utility of the semi-automated analysis of the TTC staining (SAT) software program, a novel, small, user-friendly, and free software program, in the quantification of the infarct size in rodent brain sections, with TTC staining, by analyzing images captured by cell phones or scan systems. We performed MCAO and TTC staining in adult mice. We then utilized the SAT software and Image J to analyze the infarct size in the brain sections with TTC staining and compared the findings of the two analysis methods. We found that the data on infarct size from SAT and from Image J were comparable, suggesting that the SAT software could be an alternative option to Image J in the evaluation of ischemic stroke.

Fast quantitative fluorescence authentication of milk powder and vanillin by a line-scan hyperspectral system.

We present a fast hyperspectral line-scan fluorescence imaging system to verify the feasibility of quantitative fluorescence authentication of powders. Vanillin, which is restricted for use in milk powder, especially in milk powder for infants, is mixed with milk powder in different mass concentrations (5%, 10%, 30%, 50%, 70%, and 90%). Mixed powders are located on a motorized linear stage. A 405 nm line laser is utilized to excite the fluorescence of the sample. Based on galvo scanning, we can generate a laser line with high spatial resolution and high-intensity density on the samples. An imaging spectrometer with a complementary metal-oxide semiconductor (CMOS) camera as detector is built. The spectral range of the spectrometer is 365-810 nm, with about 1 nm spectral resolution. One snapshot of the CMOS can acquire the fluorescent spatial and spectral information of a line region in 100 ms. By scanning the motorized linear stage, we obtain the fluorescence hypercube of the sample. A 100×1926×1216 hypercube, which covers an area of 15 mm×5 mm, is obtained in 50 s. The imaging speed can be enhanced further by increasing the intensity of the excitation laser and the sensitivity of the area camera. Fully constrained least squares, a linear spectral mixture analysis, is utilized to analyze the hypercube obtained by our homemade imaging spectrometer, thus obtaining the pixel concentration of vanillin in each mixed powder. Linear regression analysis is used for the pixel concentration and mass concentration of vanillin. A linear relationship with coefficient of determination R2 equal to one is observed, which demonstrates the capability of fluorescence hyperspectral quantitative analysis in powders.

Aggregation-Induced Emission Luminogen with Near-Infrared-II Excitation and Near-Infrared-I Emission for Ultradeep Intravital Two-Photon Microscopy.

Currently, a serious problem obstructing the large-scale clinical applications of fluorescence technique is the shallow penetration depth. Two-photon fluorescence microscopic imaging with excitation in the longer-wavelength near-infrared (NIR) region (>1100 nm) and emission in the NIR-I region (650-950 nm) is a good choice to realize deep-tissue and high-resolution imaging. Here, we report ultradeep two-photon fluorescence bioimaging with 1300 nm NIR-II excitation and NIR-I emission (peak ∼810 nm) based on a NIR aggregation-induced emission luminogen (AIEgen). The crab-shaped AIEgen possesses a planar core structure and several twisting phenyl/naphthyl rotators, affording both high fluorescence quantum yield and efficient two-photon activity. The organic AIE dots show high stability, good biocompatibility, and a large two-photon absorption cross section of 1.22 × 103 GM. Under 1300 nm NIR-II excitation, in vivo two-photon fluorescence microscopic imaging helps to reconstruct the 3D vasculature with a high spatial resolution of sub-3.5 µm beyond the white matter (>840 µm) and even to the hippocampus (>960 µm) and visualize small vessels of ∼5 µm as deep as 1065 µm in mouse brain, which is among the largest penetration depths and best spatial resolution of in vivo two-photon imaging. Rational comparison with the AIE dots manifests that two-photon imaging outperforms the one-photon mode for high-resolution deep imaging. This work will inspire more sight and insight into the development of efficient NIR fluorophores for deep-tissue biomedical imaging.

Experimental Demonstration of Remote and Compact Imaging Spectrometer Based on Mobile Devices.

Imaging spectrometers show great potential for environmental and biomedical sensing applications. Selfie sticks, which are tools used to take photographs or videos, have gained global popularity in recent years. Few people have connected these two objects, and few people have researched the application of imaging spectrometers to perform scientific monitoring in point-of-use scenarios. In this paper, we develop a compact imaging spectrometer (35 g in weight, 18 mm in diameter, and 72 mm in length) that can be equipped on a motorized selfie stick to perform remote sensing. We applied this system to perform environmental and facial remote sensing via motorized scanning. The absorption of chlorophyll and hemoglobin can be found in the reflectance spectra, indicating that our system can be used in urban greening monitoring and point-of-care testing. In addition, this compact imaging spectrometer was also easily attached to an underwater dome port and a quad-rotor unmanned aerial vehicle to perform underwater and airborne spectral detection. Our system offers a route toward mobile imaging spectrometers used in daily life.

A mobile device-based imaging spectrometer for environmental monitoring by attaching a lightweight small module to a commercial digital camera.

Spatially-explicit data are essential for remote sensing of ecological phenomena. Lately, recent innovations in mobile device platforms have led to an upsurge in on-site rapid detection. For instance, CMOS chips in smart phones and digital cameras serve as excellent sensors for scientific research. In this paper, a mobile device-based imaging spectrometer module (weighing about 99 g) is developed and equipped on a Single Lens Reflex camera. Utilizing this lightweight module, as well as commonly used photographic equipment, we demonstrate its utility through a series of on-site multispectral imaging, including ocean (or lake) water-color sensing and plant reflectance measurement. Based on the experiments we obtain 3D spectral image cubes, which can be further analyzed for environmental monitoring. Moreover, our system can be applied to many kinds of cameras, e.g., aerial camera and underwater camera. Therefore, any camera can be upgraded to an imaging spectrometer with the help of our miniaturized module. We believe it has the potential to become a versatile tool for on-site investigation into many applications.

Pencil-like imaging spectrometer for bio-samples sensing.

Spectrally-resolved imaging techniques are becoming central to the investigation of bio-samples. In this paper, we demonstrate the use of a WIFI-camera as a detection module to assemble a pencil-like imaging spectrometer, which weighs only 140 g and has a size of 3.1 cm in diameter and 15.5 cm in length. The spectrometer is standalone, and works wirelessly. A smartphone or network computer can serve as the data receiver and processor. The wavelength resolution of the spectrometer is about 17 nm, providing repeatable measurements of spatial two-dimensional images at various wavelengths for various bio-samples, including bananas, meat, and human hands. The detected spectral range is 400 nm - 675 nm and a white LED array lamp is selected as the light source. Based on the detected spectra, we can monitor the impacts of chlorophyll, myoglobin, and hemoglobin on bananas, pork, and human hands, respectively. For human hand scanning, a 3D spectral image data cube, which exhibits excellent signal to background noise ratio, can be obtained within 16 sec. We envisage that the adaptation of imaging spectrometer devices to the widely-accepted smartphone technology will help to carry out on-site studies in various applications. Besides, our pencil-like imaging spectrometer is cost-effective (<$300) and easy to assemble. This portable imaging spectrometer can facilitate the collection of large amounts of spectral image data. With the help of machine learning, we can realize object recognition based on spectral classification in the future.

Red emissive AIE nanodots with high two-photon absorption efficiency at 1040 nm for deep-tissue in vivo imaging.

Deep-tissue penetration is highly required in in vivo optical bioimaging. We synthesized a type of red emissive fluorophore BT with aggregation-induced emission (AIE) property. BT molecules were then encapsulated with amphiphilic polymers to form nanodots, and a large two-photon absorption (2PA) cross-section of 2.9 × 10(6) GM at 1040 nm was observed from each BT nanodot, which was much larger than those at the wavelengths of 770 to 860 nm. In addition, 1040 nm light was found to have better penetration and focusing capability than 800 nm light in biological tissue, according to the Monte Carlo simulation. The toxicity and tissue distribution of BT nanodots were studied, and they were found to have good biocompatibility. BT nanodots were then utilized for in vivo imaging of mouse ear and brain, and an imaging depth of 700 µm was obtained with the femtosecond (fs) excitation of 1040 nm. The red emissive AIE nanodots with high 2PA efficiency at 1040 nm would be useful for deep-tissue functional bioimaging in the future.

Low photobleaching and high emission depletion efficiency: the potential of AIE luminogen as fluorescent probe for STED microscopy.

We present a preliminary study which explores the potential of aggregation-induced emission (AIE) luminogen as a new fluorescent probe for STED microscopy. Compared with Coumarin 102, which is a commonly used organic fluorophore in STED microscopy, HPS, a typical AIE luminogen, is more resistant to photobleaching. In addition, HPS-doped nanoparticles have higher emission depletion efficiency than Coumarin 102 in organic solution. These two advantages of AIE luminogen can facilitate the improvement of spatial resolution, as well as long-term imaging, in STED microscopy. AIE luminogen will be a promising candidate for STED microscopy in the future.

High-order non-linear optical effects in organic luminogens with aggregation-induced emission.

2,3-bis(4-(phenyl(4-(1,2,2-triphenylvinyl)phenyl)amino)phenyl)fumaronitrile (TTF) shows unique aggregation-induced emission (AIE) characteristics. Under the excitation of a 1560 nm femtosecond laser, simultaneous three-photon-excited luminescence (3PL) and third-harmonic-generation signals can be observed from its nanoaggregate and the solid state. TTF is further encapsulated with DSPE-mPEG (a type of amphiphilic polymer) to form AIE-active nanoparticles. 3PL brain imaging of mice is achieved based on the nanoparticles.